code: def transformation(self, out_batch_x: Tensor, emb):
      out = emb
      out += self.lin(out_batch_x)
      return out
  
imports: from itertools import product
  from typing import Optional, List
  import tqdm
  import torch
  from torch import Tensor
  import torch.nn.functional
  from torch.nn import ModuleList, Linear, BatchNorm1d
  from torch_sparse import SparseTensor
  from torch_geometric.nn import MessagePassing
  from torch_geometric.nn import PNAConv
  from torch_scatter import segment_csr
  from ..models import ScalableGNN
label_desc: Use image node_id 6 for calling the PNAConv obj's underlying member method code with example usage: obj.transformation(out_batch_x, emb) and returns: out